some stuff here
Steven Stigler (2016) in “The Seven Pillars of Statistical Wisdom”:
data table here
“OBP” as aggregate column explanation here
In the Sherlock Holmes story, The Adventure of the Dancing Men, a criminal known to one of the characters communicates with her using a childish/child-like drawing which looks like this:
| Variable #1 | Variable #2 | Chart Names | Chart Shape |
|---|---|---|---|
| Qual | None | Bar Chart |
Bar are used to show “counts” and “tallies” with respect to Qual variables. For instance, in a survey, how many people vs Gender? In a Target Audience survey on Weekly Consumption, how many low, medium, or high expenditure people?
OK, Let’s get some data to count:
And let’s for now use a pre-set Workflow in Orange
Qualitative Variables
species: Species of the penguin (Qual)island: Island where the penguin was observed (Qual)sex: Male / Female penguin (Qual)Quantitative Variables
bill_length_mm: Length of the penguin’s bill in millimeters (Quant)bill_depth_mm: Depth of the penguin’s bill in millimeters (Quant)flipper_length_mm: Length of the penguin’s flipper in millimeters (Quant)body_mass_g: Mass of the penguin in grams (Quant)Counts first give you an absolute sense of how much data you have.
Counts by different Qual variables give you a sense of the combinations you have in your data: (Male/Female) * (Species) * (Island) (Say 2 * 3 * 3 = 18 combinations in the data)
Counts then give an idea whether your data is lop-sided
Since the X-axis in bar charts is Qualitative (the bars don’t touch, remember!) it is possible to sort the bars at will.
Let’s get the titanic data, using the Datasets widget in Orange.
There were 2201 passengers, as per this dataset.
And let’s use a pre-set Workflow in Orange
titanic| Variable #1 | Variable #2 | Chart Names | Chart Shape |
|---|---|---|---|
| Qual | Qual |
Here, area \sim count, so the area of the tile is proportional to the count of observations in that tile.
Note
survived with sexSo sadly Jack is far more likely to have died than Rose.
Note
first class and Jack was third class. So again the odds are stacked against him.When differences between the actual and expected counts are large, we deduce that one Qual variable has an effect on the other Qual variable. (speaking counts-wise or ratio-wise)
Why is this slide always showing up?

Arvind V.| VizChitra2025 | June 2025